Back to Authors

Wood, Ashley

https://orcid.org/0000-0002-9312-6184

Mayo Clinic

Mayo Clinic in Florida

Citations 4

The Neurofibrillary Tangle Maturity Scale: A Novel Framework for Tangle Pathology Evaluation in Alzheimer’s Disease
Moloney, Christina M. , Rutledge, Matthew H., Tranovich, Jessica F., Wood, Ashley , Rothberg, Darren M., Duara, Ranjan, Lachner, Christian , Graff‐Radford, Neill R. , Carter, Rickey E. , Murray, Melissa E. , Labuzan, Sydney A. , Peng, Zhongwei , Wood, Ashley C., Carter, Rickey E , Murray, Melissa E , Wood, Ashley C., Dickson, Dennis W. , Kanaan, Nicholas M.

No container title available | June 6, 2025 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1101/2025.06.02.657435 Get It

Abstract Neurofibrillary tangles are dynamic neuropathologic hallmarks of Alzheimer’s disease with a hypothesized lifespan morphologically-defined by three maturity levels: pretangles, mature tangles, and ghost tangles. To better understand the progression of tangle pathophysiology, we characterized tangle maturity level predilection of 15 tau antibodies recognizing a broad range of linear, phosphorylation, conformational, and truncation epitopes in the hippocampus of 24 postmortem brains. We developed the tangle maturity scoring system to semi-quantitatively evaluate each tangle maturity level. Based on proportions of tangle maturity levels, we classified antibodies as “early” (mostly pretangles and mature tangles), “middling” (mature tangles with pretangles and ghost tangles), and “advanced” (mostly ghost tangles and mature tangles) tangle maturity markers. To summarize tangle maturity predilection, we developed the tangle maturity scale to integrate individual tangle maturity scores. Correlations showed stronger relationships between tangle maturity scale and subsector thickness for more advanced tangle maturity markers in CA1 and subiculum, whereas Braak tangle stage remained consistently correlated throughout markers of the tangle lifespan. To aid in scoring hippocampi, we used machine learning to recognize tangle maturity levels, which performed comparably to a domain expert and showed similar relationships by Spearman correlation. Pattern recognition software was used to assess tangle and neuritic tau burden separately, which generally correlated with Braak stage and neuronal counts. However, tangle-derived tau burden more consistently correlated with hippocampal subsector thickness. In conclusion, we developed manual and automated scoring systems to evaluate tangle maturity levels, demonstrating early 4R, phosphorylated, and oligomeric tau accumulation preceding more advanced 3R and truncated tau. Our study provides supportive evidence of disease-relevant ordering of tau posttranslational modifications in the brain, which may have implications for theragnostic development. These findings underscore the promise of computerized quantitative analyses (i.e., pathomics) for high-throughput feature extraction from whole-slide images to enhance our understanding of microscopically observed morphologic changes.
Neurofibrillary tangle characterization in the olfactory bulb among clinicopathologic subtypes of Alzheimer’s disease
Chalk, Jessica L , Kwan, Rain , Martin, Nicholas B. , Dunlop, Sara , Rothberg, Darren M., Wood, Ashley , Tranovich, Jessica F., Duara, Ranjan, Graff‐Radford, Neill R. , Moloney, Christina M. , Boon, Baayla D.C. , Wood, Ashley C., Dickson, Dennis W. , Murray, Melissa E.

Alzheimer's & Dementia | January 9, 2025 | Volume: 20 | Issue: S8 | Pages: No page available

10.1002/alz.095134 Get It

AbstractBackgroundAlzheimer’s disease (AD) is neuropathologically heterogeneous and can be objectively classified along a spectrum of corticolimbic tangle distribution as hippocampal sparing (HpSp) AD, typical AD, and limbic predominant AD. The olfactory bulb is an early area of tau accumulation with a direct connection to the amygdala. Although tau pathology has been identified in the olfactory bulb, its association with AD subtypes remains unclear. To investigate these differences, tau markers were characterized within the olfactory bulb among AD subtypes.MethodThe cohort included 39 AD cases (HpSp AD: n = 15, typical AD: n = 12, limbic AD: n = 12). Immunofluorescence staining was conducted on 5 µm thick formalin‐fixed paraffin‐embedded olfactory bulb sections using phosphorylated tau (AT8 & PHF‐1) and C‐terminal tau (2E9) antibodies. Slides were digitally scanned on the PhenoImager™ HT slide scanner and analyzed using QuPath Digital Analysis software, quantifying tau burden as a percentage of positive staining.ResultIn whole olfactory bulbs, AT8 was observed as intrasomal tangle‐like immunoreactivity with some extrasomal neuritic staining. AT8 burden did not differ among subtypes (HpSp AD median = 0.28% [interquartile range 0.014‐1.7%], typical AD = 0.28% [0.027‐2.24%], limbic AD = 0.39% [interquartile range 0.39‐0.74%]). PHF‐1 was observed as intrasomal tangle‐like immunoreactivity with abundant extrasomal neuritic pathology. PHF‐1 was observed to be highest in limbic AD (HpSp AD = 3.5% [0.63‐11%)], typical AD = 3.2% [0.38‐13%], and limbic AD = 5.3% [1.97‐10%]) and differed from typical AD (p<0.05). 2E9 was observed as intrasomal tangle‐like immunoreactivity with minimal extrasomal staining and not found to differ among subtypes (HpSp AD = 0.18% [0.036‐2.2%], typical AD = 0.15% [0.021‐2.4%], and limbic AD = 0.29% [0.0030‐8.2%]).ConclusionAbundant tau accumulation was observed among all AD subtypes with some suggestion of higher tau burden in limbic predominant AD. Given the direct connection between olfactory bulb and amygdala, it is interesting to speculate of an environmental contribution to limbic predominant AD through olfactory bulb damage. Future studies will expand the cohort to include AD cases with Lewy body disease co‐pathology and primary tauopathies with a focus on the anterior olfactory nucleus as the primary site of tau pathology.
Clinicopathologic Heterogeneity and Glial Activation Patterns in Alzheimer Disease
Frankenhauser, Isabelle , Peng, Zhongwei , Labuzan, Sydney A. , Boon, Baayla D.C. , Moloney, Christina M. , Pottier, Cyril , Wickland, Daniel P. , Tranovich, Jessica F., Wood, Ashley , Hinkle, Kelly M., Lincoln, Sarah, Spychalla, Anthony J., Przybelski, Scott A. , Kwan, Rain S., Lesser, Elizabeth R. , Carter, Rickey E. , Ross, Owen A. , Lachner, Christian , Ertekin‐Taner, Nilüfer , Ferman, Tanis J. , Fields, Julie A. , Nguyen, Aivi T. , Reichard, R. Ross , Graff‐Radford, Jonathan , Petersen, Ronald C. , Jack, Clifford R. , Kantarci, Kejal , Day, Gregory S. , Duara, Ranjan , Graff‐Radford, Neill R. , Lowe, Val J. , Murray, Melissa E. , Kouri, Naomi , Caetano-Anolles, Kelsey, Corriveau-Lecavalier, Nick , Wood, Ashley C., Lincoln, Sarah J, Engelberg-Cook, Erica , Crook, Julia E. , Jack, Clifford R , Ross, Owen A , Carter, Rickey E , Kantarci, Kejal , Day, Gregory S , Murray, Melissa E , Ferman, Tanis J , Nguyen, Aivi T , Pottier, Cyril , Caetano-Anollés, Kelsey , Corriveau‐Lecavalier, Nick , Wood, Ashley C., Senjem, Matthew L. , Schwarz, Christopher G. , Machulda, Mary M. , Ramanan, Vijay K. , Jones, David T. , Boeve, Bradley F. , Knopman, David S. , Duara, Ranjan , Dickson, Dennis W. , Vemuri, Prashanthi

JAMA Neurology | April 15, 2024 | Volume: 81 | Issue: 6 | Pages: 619

10.1001/jamaneurol.2024.0784 Get It

Importance Factors associated with clinical heterogeneity in Alzheimer disease (AD) lay along a continuum hypothesized to associate with tangle distribution and are relevant for understanding glial activation considerations in therapeutic advancement. Objectives To examine clinicopathologic and neuroimaging characteristics of disease heterogeneity in AD along a quantitative continuum using the corticolimbic index (CLix) to account for individuality of spatially distributed tangles found at autopsy. Design, Setting, and Participants This cross-sectional study was a retrospective medical record review performed on the Florida Autopsied Multiethnic (FLAME) cohort accessioned from 1991 to 2020. Data were analyzed from December 2022 to December 2023. Structural magnetic resonance imaging (MRI) and tau positron emission tomography (PET) were evaluated in an independent neuroimaging group. The FLAME cohort includes 2809 autopsied individuals; included in this study were neuropathologically diagnosed AD cases (FLAME-AD). A digital pathology subgroup of FLAME-AD cases was derived for glial activation analyses. Main Outcomes and Measures Clinicopathologic factors of heterogeneity that inform patient history and neuropathologic evaluation of AD; CLix score (lower, relative cortical predominance/hippocampal sparing vs higher, relative cortical sparing/limbic predominant cases); neuroimaging measures (ie, structural MRI and tau-PET). Results Of the 2809 autopsied individuals in the FLAME cohort, 1361 neuropathologically diagnosed AD cases were evaluated. A digital pathology subgroup included 60 FLAME-AD cases. The independent neuroimaging group included 93 cases. Among the 1361 FLAME-AD cases, 633 were male (47%; median [range] age at death, 81 [54-96] years) and 728 were female (53%; median [range] age at death, 81 [53-102] years). A younger symptomatic onset (Spearman ρ = 0.39, P &amp;lt; .001) and faster decline on the Mini-Mental State Examination (Spearman ρ = 0.27; P &amp;lt; .001) correlated with a lower CLix score in FLAME-AD series. Cases with a nonamnestic syndrome had lower CLix scores (median [IQR], 13 [9-18]) vs not (median [IQR], 21 [15-27]; P &amp;lt; .001). Hippocampal MRI volume (Spearman ρ = −0.45; P &amp;lt; .001) and flortaucipir tau-PET uptake in posterior cingulate and precuneus cortex (Spearman ρ = −0.74; P &amp;lt; .001) inversely correlated with CLix score. Although AD cases with a CLix score less than 10 had higher cortical tangle count, we found lower percentage of CD68-activated microglia/macrophage burden (median [IQR], 0.46% [0.32%-0.75%]) compared with cases with a CLix score of 10 to 30 (median [IQR], 0.75% [0.51%-0.98%]) and on par with a CLix score of 30 or greater (median [IQR], 0.40% [0.32%-0.57%]; P = .02). Conclusions and Relevance Findings show that AD heterogeneity exists along a continuum of corticolimbic tangle distribution. Reduced CD68 burden may signify an underappreciated association between tau accumulation and microglia/macrophages activation that should be considered in personalized therapy for immune dysregulation.
Tangle and neuritic burden from neurofibrillary tangle maturity markers in the hippocampus are differentially correlated to tau‐PET, MRI, and cognitive measures
Peng, Zhongwei , Wood, Ashley , Rothberg, Darren M., Rutledge, Matthew H., Hofrenning, Ekaterina I. , Petersen, Ronald C. , Reichard, Ross R., Lowe, Val J. , Moloney, Christina M. , Wood, Ashley C., Machulda, Mary M. , Jack, Clifford R. , Dickson, Dennis W. , Nguyen, Aivi T. , Carter, Rickey E. , Vemuri, Prashanthi , Murray, Melissa E.

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S15 | Pages: No page available

10.1002/alz.077920 Get It

AbstractBackgroundThere is a gap in knowledge concerning which tangle maturity levels (Moloney, Alzheimers Dement, 2021) are associated with antemortem measures (tau‐PET, MRI, cognitive testing). We hypothesized antemortem measures would be more strongly correlated with markers recognizing middling to advanced tangle maturity. We additionally sought to assess the strength of the relationship with tangle and neuritic pathology recognized by tangle maturity markers.MethodPosterior hippocampi from n = 30 cases with antemortem measures ≤3 years prior to death were cut (5µm) and immunostained with tau antibodies to evaluate early (AT8), middling (PHF‐1), or advanced (2E9) tangle maturity. GENIE (pattern recognition software) separated tangle from neuritic burden (Figure). Hippocampus, parahippocampus, and fusiform were analyzed to correlate digital pathology with flortaucipir tau‐PET standard uptake value ratio (SUVr, cerebellar crus normalization), MRI volume/thickness, and cognitive measures which included Auditory Verbal Learning Test (AVLT) delayed recall, Mini‐Mental State Exam (MMSE), and Clinical Dementia Rating (CDR).ResultThe strongest relationships observed with flortaucipir were with PHF‐1 and 2E9 burden (Table). AT8 tangle and neuritic burden correlations with flortaucipir were relatively similar in the hippocampus but were stronger with neuritic pathology in parahippocampus and fusiform. PHF‐1 tangle and neuritic burden correlations were relatively similar with flortaucipir. 2E9 correlations were stronger with neuritic pathology in hippocampus. MRI measures were more strongly correlated with PHF‐1 and 2E9 burden. AT8 tangle and neuritic burden were correlated with fusiform thickness. The correlations between MRI measures and 2E9 tangle and neuritic burden were similar. Correlations between cognitive measures were similar between tangle maturity markers. AVLT delayed recall correlated with all tangle maturity markers, but neuritic burden was stronger for AT8 and 2E9 in hippocampus compared to tangle burden. MMSE correlated with neuritic burden for all tangle maturity markers. CDR remained statistically non‐significant.ConclusionInterpretation of the strength of the relationship between tau burden and antemortem measures differed across tangle maturity markers. Neuroimaging measures may be more sensitive to middle/advanced maturity markers with limited differences between tangle and neuritic pathology. These findings may be biologically relevant and imply either a limited recognition of tangles depending on antibody epitope, and/or may represent the clinicoradiologic impact of increasing neuritic burden.